Blood and MRI biomarkers of mild traumatic brain injury in non-concussed collegiate football players

Football has one of the highest incidence rates of mild traumatic brain injury (mTBI) among contact sports; however, the effects of repeated sub-concussive head impacts on brain structure and function remain under-studied. We assessed the association between biomarkers of mTBI and structural and functional MRI scans over an entire season among non-concussed NCAA Division I linemen and non-linemen. Concentrations of S100B, GFAP, BDNF, NFL, and NSE were assessed in 48 collegiate football players (32 linemen; 16 non-linemen) before the start of pre-season training (pre-camp), at the end of pre-season training (pre-season), and at the end of the competitive season (post-season). Changes in brain structure and function were assessed in a sub-sample of 11 linemen and 6 non-linemen using structural and functional MRI during the execution of Stroop and attention network tasks. S100B, GFAP and BDNF concentrations were increased at post-season compared to pre-camp in linemen. White matter hyperintensities increased in linemen during pre-season camp training compared to pre-camp. This study showed that the effects of repeated head impacts are detectable in the blood of elite level non-concussed collegiate football players exposed to low-moderate impacts to the heads, which correlated with some neurological outcomes without translating to clinically-relevant changes in brain anatomy or function.


Structural MRI changes throughout the season
Changes in grey matter, white matter, cerebrospinal fluid (CSF), and white matter hyperintensities (WMH) volumes throughout the season are presented in Fig. 2 and Supplementary Table S2.Throughout the study, linemen and non-linemen presented no difference in structural MRI variables, including grey matter, white matter, and CSF (p > 0.05 for all).However, while no differences were found in white matter hyperintensities between linemen and non-linemen (p = 0.43) throughout the season, white matter hyperintensities increased in linemen during pre-season camp training (p < 0.05) before coming back to pre-camp levels at the end of the season (p < 0.01).Mean white matter fractional anisotropy (FA) and mean white matter mean diffusivity (MD) are presented in Supplementary Table S3.No changes were detected in FA and MD over the course of the season and between linemen and non-linemen (p = 0.90, p = 0.89, respectively).

Stroop tasks
Reaction time (RT) to congruent stimuli during the Stroop task decreased throughout the season in both linemen and non-linemen (p < 0.0001) (Fig. 3f), with no difference between the groups throughout the season (p = 0.14).Linemen showed faster responses to incongruent trials over time (pre-camp vs. post-camp training: p < 0.0001; post-camp training vs. post-season: p < 0.05), while non-linemen showed slowest RTs at pre-camp, and faster at post-camp training (p < 0.05), and neither faster nor slower at the post-season (p = 0.91) (Fig. 3g).Although the accuracy of the Stroop task was not different between the groups at pre-camp (p = 0.23), non-linemen showed higher task accuracy at the end of the pre-season training camp than linemen (p < 0.01).Interestingly, these differences in task accuracy between the two groups disappeared at the end of the season (p = 0.25).Finally, Stroop task fMRI activation in the occipital gyrus was higher in non-linemen than linemen at pre-camp (p < 0.05) but over time, non-linemen group went down, having comparable activation between linemen and non-linemen at post-season (p = 0.24).

Attention network test (ANT)
Changes in reaction time for the different ANT trial types over the study period are presented in Fig. 3.No differences in RT were found in response to any ANT trial type, including congruent, incongruent, no cue, center cue, and spatial cue between linemen and non-linemen throughout the study (p = 0.12, p = 0.15, p = 0.16, p = 0.17, www.nature.com/scientificreports/p = 0.09, respectively).Furthermore, ANT accuracy was similar between the groups at all time points (pre-camp: p = 0.55, post-camp: p = 0.12, post-season: p = 0.24, respectively).fMRI activation to the ANT task in the right thalamus region (p < 0.01) and right superior parietal lobe (p < 0.01) increased between pre-camp and the end of pre-season training camp in linemen, and increased in the left fusiform gyrus (p < 0.01) with concomitant decreases in the left superior frontal gyrus between the end of pre-season training camp and post-season among linemen (p < 0.01), but not among non-linemen.Similarly, linemen exhibited higher activation in the left superior frontal gyrus compared to non-linemen at pre-camp (p < 0.05), but the differences disappeared at the end of pre-season camp (p = 0.08) and post-season (p = 0.75).In addition, non-linemen showed decreased activations in the left inferior frontal gyrus region from pre-camp to pre-season (p < 0.05), while no differences were detected between the groups throughout the season (p = 0.52).

Correlation with biomarkers of mTBI and brain imaging
To further investigate the potential links between circulating biomarkers of mTBI included in this study and the brain imaging outcomes, we characterized the correlations between BDNF, S100B, NFL, NSE, and GFAP with the sMRI (i.e.normalized gray matter, normalized white matter, normalized white matter hyperintensities, normalized CSF) and fMRI (ANT, Stroop) outcomes using data aggregated from all timepoints.When all data were aggregated (pre-camp, pre-season training camp, and post-season, regardless of group), and accounted for repeated measures, greater circulating S100B (r 2 = 0.076, p < 0.05) levels was associated with an increase in normalized total white matter, showing that players with higher S100B also had higher volumes of total white matter (Fig. 4).When assessing group differences between NSE and sMRI data, a higher NSE levels in linemen were associated with lesser normalized total white matter, while a higher NSE was associated with a higher volume of total white matter in non-linemen (t = −2.82,p < 0.05) (Fig. 4).On the other hand, greater circulating BDNF levels were associated with a lower normalized cerebral spinal fluid volume (CSF) (r 2 = 0.16, p < 0.01), and a higher circulating NSE levels (r 2 = 0.18, p < 0.05) were associated with a higher normalized CSF, regardless of group and timepoint (Fig. 4).In addition, a positive trend was observed between S100B concentrations and normalized white matter hypersensitivity (r 2 = 0.08, p < 0.05), as well as between NFL levels and normalized total gray matter (r 2 = 0.37, p < 0.01) in all players.

Correlation between biomarkers and functional Magnetic resonance imaging (MRI)
No associations were found between changes in biomarker concentrations and fMRI outcomes during either camp or season in isolation (p > 0.05 for all).Consequently, data from all time points were aggregated and correlations accounting for repeated measures were calculated to increase statistical power.

Attention network task (ANT)
When analyzing data independently of timepoint, higher levels of serum BDNF were associated with slower ANT congruent RT in linemen while the opposite was true in non-linemen where higher BDNF levels were indicative  www.nature.com/scientificreports/ of faster ANT congruent RT (r 2 = 0.12, p < 0.05) (Fig. 5).Similarly, on ANT incongruent (r 2 = 0.08, p < 0.05), no cue (r 2 = 0.14, p < 0.01), and center cue tasks (r 2 = 0.08, p < 0.05), higher BDNF levels were associated with slower RT on those tasks in linemen, while non-linemen players exhibiting higher BDNF levels also displayed faster RT on those tasks than those with lower levels of circulating BDNF (Fig. 5).

Stroop
We found greater concentrations of GFAP levels were associated with greater Stroop congruent trial RT (r 2 = 0.42, p < 0.01), along with Stroop incongruent trials (r 2 = 0.35, p < 0.01) (Fig. 6).In addition, greater concentrations of GFAP were observed in non-linemen who were slower on the congruent trials.Also in linemen, lower circulating GFAP was associated with slower Stroop RT (t = −3.14, p < 0.01).Similarly, while greater circulating GFAP was associated with slower RT on Stroop incongruent trials in non-linemen, low circulating GFAP was associated with slower RT in linemen (t = −2.28,p < 0.05) (Fig. 6).Moreover, a positive trend was found with linemen tending to have slower RT on Stroop incongruent tasks than non-linemen (r 2 = 0.18, p = 0.058).
A positive correlation was found between NFL concentrations and RT on Stroop congruent tasks (r 2 = 0.34, p < 0.05), and on RT on Stroop incongruent trial tasks (r 2 = 0.10, p < 0.01) (Fig. 6), suggesting higher NFL  www.nature.com/scientificreports/concentrations were associated with slower RT on both tasks.Of note, the association between NFL levels and Stroop incongruent RT was stronger in non-linemen than linemen, with those who exhibited greater circulating NFL concentrations also demonstrating the slowest incongruent RT (t = −3.74,p < 0.05) (Fig. 6).S100b and NSE were not correlated with any of ANT or Stroop tasks (p > 0.05 for all).

Discussion
High-impact sports such as American football are associated with repeated head collisions that vary in number, magnitude, and velocity based on players' position.Moderate to high amplitude impacts to the head in competitive football players often lead to concussions and likely promote acute and chronic neurological impairments 1,2 .
Since the rapid and accurate diagnosis of concussion can improve clinical outcomes 1,2 , numerous studies have attempted to identify blood biomarkers of mTBI in both athletes 4,8,10,11 , and trauma patients 5,9 .While some brain-derived proteins appear to be detectable in the blood of patients with severe TBI 8,10 , their sensitivity in diagnosing mTBI from non-concussive impacts in athletes who experience lower magnitude head impact is less clear.This is especially true in American football players exposed to repeated low-moderate intensity impacts to the head throughout regular training and competitive seasons.Therefore, we aimed to characterize changes in several blood biomarkers of mTBI along with their association with structural and functional MRI in elitelevel collegiate football players exposed to repeated sub-concussive impacts to the head due to their position throughout the course of a season.In this study, we found that linemen exhibited greater levels of circulating S100B, GFAP, and BDNF after a competitive season compared to pre-camp season levels.Considering that no players were diagnosed with a concussion during the study period, physical activity itself may be sufficient to induce changes in circulating biomarkers of brain trauma.Indeed, some of the proteins included in this study, such as S100B, have been shown to increase in elite swimmers after a long-distance swim competition, indicating that exercise itself can elevate some of these proteins in circulation, independently of any impact to the head 12 .
Previous studies reported increases in brain-borne proteins in circulation after concussive and sub-concussive trauma, including S100B 6,11 , GFAP 6,9 , NSE 6,7,10 , NFL 6,8 , and BDNF 13 .Among these, S100B is released by astrocytes in response to brain injury and remains elevated 24-48 h following concussion 1,5,6 .GFAP is also a cytoskeletal intermediate filament protein expressed by astrocytes, highly abundant in the brain, and elevated levels of GFAP were found in mild to moderate TBI patients compared to uninjured controls 5,9 .When comparing these proteins, studies have suggested that GFAP may be more sensitive in detecting intracranial CT lesions compared to S100B 9 .Interestingly, compared to pre-camp, we showed elevations in both S100B and GFAP at the end of the competitive season.We also found a positive correlation between the levels of circulating S100B and white matter hyperintensities, a predictor of risk of stroke and cognitive impairments 13 .It is however important to highlight that white matter hypersensitivity in linemen at post-camp training was as high as those reported in non-athletic populations in other studies 14 .The lack of association between S100B and any functional neuroimaging outcomes in the present study does not enable us to draw meaningful conclusions advocating for any neurological dysfunction to have occurred in the linemen.In contrast, we also found that GFAP levels and RTs of Stroop tasks both in congruent and incongruent trials were in the intuitive direction-higher level of GFAP, worse RT which are non-invasive measurements eliciting cognitive function measuring selective attention 15 .While we were unable to adequately capture accurate data on the magnitude and number of hits to the head during games, we hypothesize that these increases in blood biomarkers could be due to repeated exposures to in-training and in-game head impacts.However, there was no association between the changes in circulating S100B and GFAP levels and the changes in mean values of sMRI or fMRI outcome.S100B and GFAP can be released in the blood in response to low-moderate impacts to the head and subsequent disruption of the blood-brain barrier, without being associated with neurological impairments, therefore limiting their diagnostical validity to identify mTBI 1,2,6 .
NSE is a promising surrogate marker for neuronal injury.Serum NSE has been shown to remain chronically elevated for up to 2 months after sport cessation in boxers who experienced repetitive head blows 7 , even in the absence of mTBI.As such, clinical validation between repetitive head trauma and elevated levels of NSE is required before asserting its usefulness as a diagnostic tool 10 .NFL, a member of the family of intermediate filament proteins, is a biomarker of axonal injury in the brain and has been reported to be elevated throughout the football season in collegiate football athletes 8 .Throughout the season, we found no changes in these biomarkers.However, greater NSE concentration was associated with the lesser normal appearing white matter in linemen while greater NSE was associated with the greater normal appearing white matter in non-linemen, which requires further investigation.One possible explanation could be that loss of white matter connections is related to the NSE concentrations.We recognize that this association may not be clinically-relevant since normal appearing white matter did not change during the season, and no associations were observed between the changes in NSE and the changes in structural MRI.
BDNF is a neurotrophic protein that plays a role in the survival, plasticity, and growth of neurons and has been shown to be increased in severe TBI compared to mild or moderate TBI 8 .However, due to the properties of BDNF, elevated BDNF concentration in the peripheral blood can have dichotomic origins.In the present study, BDNF levels were associated with ANT tasks in a group-dependent manner.Specifically, non-linemen with higher BDNF levels also exhibited faster RT on the ANT task, while linemen with higher BDNF had slower RT when performing the same task.These correlations may suggest that elevation of BDNF is associated with neural impairments due to neural damage in athletes who frequently experience low-moderate intensity impacts to the head while also being associated with improved neurological functioning in athletes who exercise but do not get hit frequently.However, we remain cautious and should not over-interpret these data without actual head impact records.Indeed, this could also be indicative of normal and healthy brain repair in response to damages induced by repeated impacts, or a natural consequence of the higher level of physical fitness in our population 16 .Especially, while S100B has been suggested to be one of the strongest biomarkers to detect head injuries, previous www.nature.com/scientificreports/studies on athletes competing in non-contract sports such as swimming, running and basketball 12,17,18 showed increased level of S100B independently of head impact history.Thus, it can be argued that none of the biomarkers included in this study are sufficient to be used as clinically-relevant diagnostic tools of mTBI.
Our study has limitations and caution should be used when interpreting the data.First, this study addressed the blood serum levels of various brain-borne proteins and their association with structural and functional MRI outcomes throughout the season in non-concussed elite-level American football athletes.However, we were unable to adequately collect head impact magnitude and numbers, thus limiting our ability to investigate the effects of a clinically-relevant range of head trauma on these outcomes as well as not including non-contact sport athletes as a control group.Due to technical constraints, a further limitation can be found in our inability to collect structural and functional MRI data on our entire study population.Finally, although this fell outside the purview of this study, future studies should aim to include concussed players in their study population.
In sum, although some studies showed that the blood biomarkers are elevated with head impact/concussion, in our study, we did not see a direct association between brain-borne proteins and sMRI and fMRI in players exposed or not to frequent head impacts.Furthermore, our study identified crucial differences in the profile of circulating biomarkers of mTBI between linemen and non-linemen over the course of a competitive season.These differences extended to brain structure, activation patterns and reaction times to the STROOP task and other functional tasks; however, these did not appear to be related to the players' position or circulating brainborne protein concentrations.Of note, our players were not diagnosed with mTBI with no classical symptoms of mTBI.However, the trends of biomarkers showed similar patterns of mTBI/concussed patients, thus our study advocates against the use of individual circulating brain-borne proteins as diagnostic tools for mTBI and concussion because of the lack of the sensitivity of biomarkers.

Participants
National Collegiate Athletic Association (NCAA) Division I football players (48 players in total: 32 linemen; 16 non-linemen) were recruited over three consecutive years in this study.All linemen and non-linemen were encouraged to enroll in the study, regardless of being on a scholarship or being a walk-on athlete.The linemen group included offensive linemen, defensive linemen, and tight ends, while the non-linemen group included defensive backs, linebackers, long snappers, punters, wide receivers, kickers, and quarterbacks.All athletes provided written informed consent, and the Institutional Review Board granted ethical approval at Louisiana State University for the study (IRB # 3902).Exclusion criteria included any conditions the team physician regarded as too risky to participate in the practices/games and any medical, psychiatric, or behavioral factors that could interfere with participating in the study.All methods were performed in accordance with the relevant guidelines and regulations.

Study design and visits
The experimental protocol consisted of three study visits: (1) pre-camp, (2) pre-season, and (3) post-season (Fig. 7).These study visits occurred (1) no more than a week before the start of training camp, (2) 24 h, and 48 h for the blood collection and sMRI and fMRI respectively after the end of the 2-week pre-season training camp, (3) 24 h, and 48 h for the blood collection and sMRI and fMRI respectively after the last game of the competitive season.During the pre-camp visit, signed informed consent was collected, height (cm) and weight (kg) were measured, blood was drawn from an antecubital vein, and sMRI and fMRI scans were conducted.The blood draw and sMRI/fMRI were repeated at pre-season and post-season visits.Participants were asked to be fasted for up to 12 h before the blood draw.All blood samples were taken 24 h after practice (pre-season) or game (post-season).sMRI and fMRI were performed 24-48 h after practice (pre-season) or game (post-season) in a single season.As for MRI scanning voluntary participation was encouraged..In each trial, for 400 to 5000 ms, participants saw one probe word and four target words that were names of colors.The task was to identify the target word whose color matched that of the probe.In the congruent (incongruent) condition, word meaning matched (did not match) the color it was printed in.Correct (incorrect) responses on three consecutive incongruent trials prompted a 300 ms reduction (increase) in stimulus duration.Four 52-60 s incongruent trial blocks were interleaved with four congruent trial blocks, each of which had the same number of trials as the previous incongruent block.The inter-block interval was 10-17 s.Stroop Task performance was summarized in terms of task accuracy (i.e., percent of trials answered correctly), mean reaction times to congruent and incongruent trials, and the so-called interference effect (i.e., the difference in mean reaction times between incongruent and congruent conditions).
Next, the Attention Network Task (ANT) was administered.In each trial of the ANT, a line of arrows was presented in one of two locations on the screen.Participants clicked a left-hand or right-hand button depending on whether the center arrow pointed to the left or right.The participant was required to suppress distracting flanker arrows on either side of the center arrow and had to process a spatial cue that appeared prior to the arrow line, either in the same location as the eventual arrow line, in both possible locations of the eventual arrow line, or not at all.The alerting score was the difference in mean reaction time (i.e., the amount of time between the presentation of the line of arrows and the button click) between trials with and without a spatial cue.The orienting score was the difference in reaction time between trials with the spatial cue in the same vs.different location as the arrow line.The executive control score was the difference in mean reaction time between trials with congruent and incongruent flankers.The total number of trials was 456.
Structural MRI data analysis.Post-processing of structural MRI data follows previously described techniques [21][22][23] .Key FLAIR processing steps include manual removal of non-brain elements from the FLAIR image by operator-guided tracing of the dura mater within the cranial vault, resulting in the delineation of a total cranial volume (TCV) region; MRI non-uniformity correction of the TCV 24 ; thresholding of TCV into brain and non-brain tissues 25 ; fitting a single Gaussian distribution to the brain tissue intensity distribution and labeling of all voxels with intensity greater than 3.5 standard deviations above the mean as WMH 26 .Key T1-weighted image processing steps include MRI non-uniformity correction 27 ; and segmentation of gray matter, white matter, and cerebrospinal fluid by a Bayesian maximum-likelihood expectation-maximization algorithm 28 .Pre-processing of diffusion MRI data followed the standardized approach taken in our earlier publications [29][30][31] .Briefly, eddy current correction was applied to gradient images through repeated co-registration using FSL flirt, the average gradient image was linearly co-registered to the average B 0 image, the average B 0 image was linearly coregistered to the corresponding T1-weighted image, and the T1-weighted image was nonlinearly deformed to a standard template space.These transformations allowed all diffusion MRI data to be placed into the standard space.Fractional anisotropy (FA) and mean diffusivity (MD) were calculated at each voxel in the native diffusion MRI space and transformed into the standard space.The primary measures of interest in subsequent analysis were volumes of total WMH, total gray matter, white matter, and cerebrospinal fluid (expressed as a percentage of TCV), and mean FA and MD across the white matter.Higher total gray matter, white matter, and mean FA, and lower WMH volume, mean MD, and cerebrospinal fluid are viewed as indicators of better brain health.
www.nature.com/scientificreports/Functional MRI changes throughout the season To further evaluate the effects of a pre-season training camp and the subsequent competitive season on brain function in linemen and non-linemen, we characterized fMRI signal changes as well as changes in response times (RT) to validated neurocognitive tasks performed during fMRI scanning, namely the Stroop and Attentional Network Test (ANT), between pre-camp and the end of pre-season training camp or the end of the season.

Figure 4 .
Figure 4. Correlations between structural MRI and biomarkers.BDNF brain derived neurotrophic factor, S100B S100 calcium binding protein B, NSE neuron-specific enolase, NFL neurofilament light chain, CSF cerebral spinal fluid, WM white matter, WMH white matter hypersensitivity, GM gray matter.

Figure 5 .
Figure 5. Correlations between ANT (attention network task) trials and BDNF within linemen and nonlinemen players.BDNF brain derived neurotrophic factor, RT reaction time.

Figure 6 .
Figure 6.Correlations between reaction time (RT) of Stroop tasks and GFAP and NFL.GFAP glial fibrillary acidic protein, NFL neurofilament light chain.

Figure 7 .
Figure 7. Schematic diagram of blood draw, structural MRI, and functional MRI time points (created with BioRender.com.)
**Difference from non-linemen group with significant set as p < 0.0001.Linemen (n = 32) Non-linemen (n = 16) * Vol.:(0123456789) Scientific Reports | (2024) 14:665 | https://doi.org/10.1038/s41598-023-51067-3 Blood sampling and biomarker analysisFasted and resting serum samples (10 mL) were collected at the same time of the day at each timepoint using vacutainer serum separator tubes (BD, Franklin Lakes, NJ).Blood samples were centrifuged and stored at − 80 °C freezer until analyses were run in batches at the end of the study.Biomarkers of brain injury including S100 calcium-binding protein B (S100B) (MyBioSource, Inc., USA), brain-derived neurotrophic factor (BDNF) (R&D System, USA), glial fibrillary acidic protein (GFAP) (R&D System, MA, USA), neurofilament light chain protein (NFL) (MyBioSource, Inc., USA), and neuron specific enolase (NSE) (R&D System, MA, USA) were measured from serum samples using quantitative Enzyme-Linked Immunosorbent Assays (ELISA).Due to low sample volume, only 26 linemen and 13 non-linemen were included in the GFAP, NSE, and NFL analysis, while S100B and BDNF were characterized on the complete dataset of 48 participants.Structural MRI, and functional MRI data collection and analysisMagnetic resonance imaging (MRI).An sMRI scan was first performed to quantify gray matter, normalappearing white matter, cerebrospinal fluid, white matter hyperintensities, and diffusion MRI measures as indices of structural brain health.An fMRI scan was also performed during the execution of two cognitive tasks (Stroop Task and the Attention Network Task) to measure task-related changes in brain activity.
fMRI tasks.First, an adaptive Stroop Task was administered to test inhibitory control in the context of negative feedback and time-pressured responses